Title:
EVENT DETECTION USING DAS FEATURES WITH MACHINE LEARNING
Document Type and Number:
WIPO Patent Application WO/2020/109427
Kind Code:
A3
Abstract:
A method of identifying events includes obtaining an acoustic signal from a sensor, determining one or more frequency domain features from the acoustic signal, providing the one or more frequency domain features as inputs to a plurality of event detection models, and determining the presence of one or more events using the plurality of event detection models. The one or more frequency domain features are obtained across a frequency range of the acoustic signal, and at least two of the plurality of event detection models are different.
Inventors:
THIRUVENKATANATHAN PRADYUMNA (GB)
Application Number:
PCT/EP2019/082809
Publication Date:
July 09, 2020
Filing Date:
November 27, 2019
Export Citation:
Assignee:
BP EXPLORATION OPERATING CO LTD (GB)
LYTT LTD (GB)
LYTT LTD (GB)
International Classes:
E21B47/107; E21B41/00; E21B47/135
Domestic Patent References:
| WO2017174746A1 | 2017-10-12 | |||
| WO2019072899A2 | 2019-04-18 | |||
| WO2016115030A1 | 2016-07-21 |
Foreign References:
| EP3006908A1 | 2016-04-13 | |||
| US20170119255A1 | 2017-05-04 |
Other References:
TATIANA SILKINA: "Application of Distributed Acoustic Sensing to Flow Regime Classification", 30 June 2014 (2014-06-30), XP055604509, Retrieved from the Internet [retrieved on 20190711]
CHRISTOPHER L STOKELY ET AL: "SPE-179151-MS Acoustics-Based Flow Monitoring During Hydraulic Fracturing", 9 February 2016 (2016-02-09), XP055338190, Retrieved from the Internet [retrieved on 20170124]
CHRISTOPHER L STOKELY ET AL: "SPE-179151-MS Acoustics-Based Flow Monitoring During Hydraulic Fracturing", 9 February 2016 (2016-02-09), XP055338190, Retrieved from the Internet
Attorney, Agent or Firm:
FORD, Louise Diane et al. (GB)
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